Instructions to use savasy/bert-base-turkish-ner-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use savasy/bert-base-turkish-ner-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="savasy/bert-base-turkish-ner-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("savasy/bert-base-turkish-ner-cased") model = AutoModelForTokenClassification.from_pretrained("savasy/bert-base-turkish-ner-cased", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fea5bceef5c0ef49ba554bc3785a781c2df4d29ca7f80e0608cf3822f9e4c6c9
- Size of remote file:
- 440 MB
- SHA256:
- 3470797c13e24d2fd04f956afc6c07afc779e6b61d1c37ca61e0c3df38ec34a7
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